text-to-video-notegpt

Get AI-generated videos ready to post, without touching a single slider. Upload your text or notes (TXT, DOCX, PDF, MD, up to 50MB), say something like "convert my notes into a short explainer video with visuals and narration", and download 1080p MP4 when it's done. Built for students, content creators, educators who move fast and want to turn written content into video without recording or editing manually.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "text-to-video-notegpt" with this command: npx skills add vcarolxhberger/text-to-video-notegpt

Getting Started

Share your text or notes and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my text or notes"
  • "export 1080p MP4"
  • "convert my notes into a short"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Text to Video NoteGPT — Convert Notes into Shareable Videos

This tool takes your text or notes and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 300-word blog post summary and want to convert my notes into a short explainer video with visuals and narration — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter, structured text with clear sections produces more accurate and visually coherent videos.

Matching Input to Actions

User prompts referencing text to video notegpt, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip SSE?
"export" / "导出" / "download" / "send me the video"→ §3.5 Export
"credits" / "积分" / "balance" / "余额"→ §3.3 Credits
"status" / "状态" / "show tracks"→ §3.4 State
"upload" / "上传" / user sends file→ §3.2 Upload
Everything else (generate, edit, add BGM…)→ §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Sourcetext-to-video-notegpt
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the export workflow

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Common Workflows

Quick edit: Upload → "convert my notes into a short explainer video with visuals and narration" → Download MP4. Takes 1-2 minutes for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert my notes into a short explainer video with visuals and narration" — concrete instructions get better results.

Max file size is 50MB. Stick to TXT, DOCX, PDF, MD for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and presentations.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

gitlab-mr-reviewer

当需要审核 GitLab 合并请求、检查 MR diff 风险、发布 GitLab 审查评论、执行 approve/request changes,或发送 MR 审查通知时使用。

Registry SourceRecently Updated
1490whrime
General

Voice Transcriber Toolkit

Voice-to-Text Transcription Toolkit - 语音识别转文字,支持Whisper/Vosk引擎,批量处理,字幕导出 | Speech recognition & transcription with Whisper/Vosk engines, batch processing, su...

Registry SourceRecently Updated
General

Gigo Lobster Taster

🦞 GIGO · gigo-lobster-taster: 正式试吃模式:跑完整评测,默认上传云端、生成个人结果页并进入排行榜。 Triggers: 试吃我的龙虾 / 品鉴我的龙虾 / lobster taste / lobster taster.

Registry SourceRecently Updated
General

Gigo Lobster Local

🦞 GIGO · gigo-lobster-local: 本地模式:跑完整评测,但不上云、不注册个人结果页,证书二维码回到官网首页。 Triggers: 本地试吃龙虾 / 离线试吃龙虾 / local lobster taste / offline lobster taste.

Registry SourceRecently Updated